中文摘要：

慢慢地移动红外线的目标的特殊特征例如包含仅仅一些象素，破相的边，低 signal-to-clutter 比率，和低速度，使他们的察觉相当困难，特别当在复杂背景沉浸时。应付这个问题，我们基于时间的目标察觉和协会策略建议一个有效红外线的目标察觉算法。首先，一个时间的目标察觉模型被开发分割感兴趣的目标。这个模型主要包含三个阶段，即，时间的过滤、时间的目标熔化，并且跨产品的过滤。然后，匹配模型的一张图被论述联系在不同时间获得的目标。协会依靠运动特征和目标，和协会操作的外观多次被执行形成能被用来帮助从随机的噪音或喧嚷引起的虚惊消解目标的连续轨道。试验性的结果证明建议方法能精确地并且要用体力地在复杂背景检测慢慢地动人的红外线的目标，并且与几个最近的方法比较有优异察觉性能。

英文摘要：

The special characteristics of slowly moving infrared targets, such as containing only a few pixels,shapeless edge, low signal-to-clutter ratio, and low speed, make their detection rather difficult, especially when immersed in complex backgrounds. To cope with this problem, we propose an effective infrared target detection algorithm based on temporal target detection and association strategy. First, a temporal target detection model is developed to segment the interested targets. This model contains mainly three stages, i.e., temporal filtering,temporal target fusion, and cross-product filtering. Then a graph matching model is presented to associate the targets obtained at different times. The association relies on the motion characteristics and appearance of targets,and the association operation is performed many times to form continuous trajectories which can be used to help disambiguate targets from false alarms caused by random noise or clutter. Experimental results show that the proposed method can detect slowly moving infrared targets in complex backgrounds accurately and robustly, and has superior detection performance in comparison with several recent methods.